Tag: API
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AI Agents with LangGraph
Introduction Agents are the next iteration of taking traditional stateless interactions with LLM’s to a stateful interaction with the use of typically Assistants API or extending using a framework. Some popular ways to create a agent workflow are tools such as Promptflow, CrewAI, LangGraph, LangChain and others. For this blog post I’m going to demonstrate…
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RouteLLM Unlocking Cost Effective LLM Routing
Introduction Costs associated with using closed-source large language models can add up in the use cases of complex tasks due to the nature of how tokens are priced for using APIs. RouteLLM is a open-sourced project that creates a method to determine based on the query a user sends which LLM to choose based on…
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Batch Jobs in Azure OpenAI
Introduction In the existing landscape of Generative AI, optimizing API submissions is crucial for both cost and performance. Whether you’re fine-tuning token usage or streamlining context-aware requests using Retrieval-Augmented Generation (RAG), finding the right tools can make a significant difference. One of the most promising solutions is the Azure OpenAI Batch API, designed specifically for…
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Adversarial Simulation in Azure AI Studio
Large Language Models present a powerful enabler for various use-cases for most enterprises but without some form of due diligence and testing can spew some unintended responses. Content safety is a preventative mechanism that is used for Azure AI Studio and can also be tested with the Prompt-flow SDK. In this blog post I’ve going…
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Vertex AI Agents
Google Cloud Platform’s Vertex AI offers a comprehensive suite of tools designed to simplify the process of building, deploying, and scaling machine learning models. One of the standout features of Vertex AI is its support for Agents, which are frameworks that enable seamless integration and automation within AI workflows. In this blog post, we’ll delve…
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API Server VNET Integration
Connectivity in AKS If you’re running AKS in production you’ll likely encounter the private link scope and integration of leverage private DNS zones for putting the API server behind private IP’s rather than accessible on port 6443 or you should be doing this. But what about other options? Perhaps you’re spinning up a dev/test cluster…
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Retina by Microsoft OSS
KubeCon 2024 in Europe has recently wrapped up this past week with some major announcements from various vendors one that stood out to me is the use of Retina. Microsoft released a open-source cloud-agnostic Kubernetes Network Observability platform this can provide a path to customizable telemetry. This telemetry has multiple options on where you’d like…
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Exploring KEDA Scaling to Zero
Continuing experimentation on CNCF projects I’ve stumbled across one that is near and dear to the Microsoft Azure space since KEDA was introduced with some contributors from Microsoft and still has maintainers that are current as of this repo’s README.md. To understand further on what exactly KEDA is we start at the top of what…
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KubeArmor Explored
KubeArmor is a cloud-native runtime security enforcement system that works with restricting behavior (this resides with execution, file access, and network operations) of pods, containers, and nodes (VM’s) at the system level. The way this tool works is by using Linux Security Modules which to no surprise are enamored in the Certified Kubernetes Security Specialist…
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Azure ML on AKS with Trusted Access
Trusted Access which is in preview provides secure access to the Kubernetes API Server while granting services that are needed for operations without requiring a traditional (private-endpoint). This feature uses the system0assigned managed identity as a authentication mechanism as intermediary to access your AKS clusters. As always in any feature that is rolled out prior…